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Consistency of nonlinear regression quantiles under Type I censoring weak dependence and general covariate design
Oberhofer, Walter; Haupt, Harry - Wirtschaftswissenschaftliche Fakultät, Universität … - 2005
For both deterministic or stochastic regressors, as well as parametric nonlinear or linear regression functions, we prove the weak consistency of the coefficient estimators for the Type I censored quantile regression model under different censoring mechanisms with censoring points depending on...
Persistent link: https://www.econbiz.de/10005607530
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Forecasting Economic Data with Neural Networks
Aminian, Farzan; Suarez, E.; Aminian, Mehran; Walz, Daniel - In: Computational Economics 28 (2006) 1, pp. 71-88
Persistent link: https://www.econbiz.de/10005701743
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Nonlinear Regression with Harris Recurrent Markov Chains
Li, Degui; Tjøstheim, Dag; Gao, Jiti - Department of Econometrics and Business Statistics, … - 2012
consider the nonlinear least squares estimators of the parameters in the homoskedastic case, and establish asymptotic theory …. We also discuss the estimation of the parameter vector in a conditional volatility function and its asymptotic theory …. Furthermore, we apply our results to the nonlinear regression with I(1) processes and establish an asymptotic distribution theory …
Persistent link: https://www.econbiz.de/10010860422
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On the accuracy of statistical procedures in Microsoft Excel 2010
Mélard, Guy - In: Computational Statistics 29 (2014) 5, pp. 1095-1128
All previous versions of Microsoft Excel until Excel 2007 have been criticized by statisticians for several reasons, including the accuracy of statistical functions, the properties of the random number generator, the quality of statistical add-ins, the weakness of the Solver for nonlinear...
Persistent link: https://www.econbiz.de/10010949800
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Nonparametric estimation via local estimating equations, with applications to nutrition calibration
Carroll, Raymond J.; Ruppert, David; Welsh, A. H. - Sonderforschungsbereich 373, Quantifikation und … - 1997
estimated via local polynomials with loess or kernel weighting, asymptotic theory is derived for the latter. In keeping with the … without deriving asymptotic theory on a case-by-case basis. The methods are applied to a series of examples. The application …
Persistent link: https://www.econbiz.de/10010956402
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A model specification test
Bartels, Knut - Sonderforschungsbereich 373, Quantifikation und … - 1998
A general model specification test of a parametric model against a nonparametric or semiparametric alternative is studied. The test statistic employs a fixed kernel, not varying by a bandwidth. This test is proved to be consistent, the asymptotic distribution is derived and shown to be...
Persistent link: https://www.econbiz.de/10010956457
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Polynomial regression and estimation function in the presence of multiplication measurement error, with application to nutrition
Iturria, Stephen J.; Carroll, Raymond J.; Firth, David - Sonderforschungsbereich 373, Quantifikation und … - 1997
In this paper we consider the polynomial regression model in the presence of multiplicative measurement error in the predictor. Consistent parameter estimates and their associated standard errors are derived. Two general methods are considered, with the methods differing in their assumptions...
Persistent link: https://www.econbiz.de/10010956460
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Nonparametric kernel and regression spline estimation in the presence of measurement error
Maca, J. D.; Carroll, Raymond J.; Ruppert, David - Sonderforschungsbereich 373, Quantifikation und … - 1997
In many regression applications both the independent and dependent variables are measured with error. When this happens, conventional parametric and nonparametric regression techniques are no longer valid. We consider two different nonparametric techniques, regression splines and kernel...
Persistent link: https://www.econbiz.de/10010956490
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MDL Mean Function Selection in Semiparametric Kernel Regression Models
Gooijer, Jan G. De; Yuan, Ao - Tinbergen Instituut - 2008
We study the problem of selecting the optimal functional form among a set of non-nested nonlinear mean functions for a semiparametric kernel based regression model. To this end we consider Rissanen's minimum description length (MDL) principle. We prove the consistency of the proposed MDL...
Persistent link: https://www.econbiz.de/10011255588
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Time Series Regression with Long Range Dependence - (Now published in 'Annals of Statistics', 25, (1997)pp.2054-2083.)
Hidalgo, Javier; Robinson, Peter M - Suntory and Toyota International Centres for Economics … - 1997
A general limit theorem is established for time series regression estimates which include generalized least squares, in the presence of long range dependence in both errors and stochastic regressors. The setting and results differ significantly from earlier work on regression with long range...
Persistent link: https://www.econbiz.de/10005310380